Exploring thermal comfort of urban buildings based on local climate zones. (15th March 2022) - Ren, Jiayi; Yang, Jun; Zhang, Yuqing; Xiao, Xiangming; Xia, Jianhong Cecilia; Li, Xueming; Wang, Shaohua
Abstract: Despite increasing attention to rising land surface temperatures (LSTs) and other climate changes caused by urbanization, few studies have considered the characteristics of LST or thermal comfort of human settlements from a regional perspective. Therefore, to explore the regional characteristics of LST and thermal comfort in Zhengzhou, China, we calculated the predicted mean vote (PMV) based on local climate zones (LCZs) using ENVI-met and studied correlations between LSTs and vegetation-type LCZs. The total land area under human settlements in Zhengzhou is 316.26 km 2, 52.72% of which is accounted by LCZs of buildings. The LSTs of built-up areas in this region were significantly higher than those of natural surfaces, with the highest and lowest LSTs of 37.98 °C (in LCZ3; compact low-rise buildings) and 32.46 °C (in LCZG; water areas), respectively. Under the same conditions, the PMV value was considered near "moderate" in areas with sparsely distributed buildings. LCZ7 (sparse high-rise buildings) always exhibited the lowest PMV, with an average value of −0.16 at 18:00 h. In addition, the correlations between LST and normalized difference vegetation index varied for LCZs with different types of vegetation, with the highest correlation coefficient (−0.80) observed in LCZA and the lowest correlation coefficient (−0.62) observed in LCZB. These results provide a reference for designing an optimal layout of urban facilities to regulate the thermal environment of human settlements and promoting urban sustainable development. Graphical abstract: Image 1 Highlights: Thermal comfort index of local climate zones in Zhengzhou, China, was analyzed. Regional land surface temperature (LST) characteristics were explored. LST o f built-up areas was significantly higher than that of natural surface. LCZ7 (sparse high-rise buildings) always exhibits the lowest predicted mean vote (PMV) value. LCZ of different vegetation types had different effects on LST.